Iterative Learning Control of an Industrial Robot for Neuromuscular Training

Publikationen: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitrag - Aufsatz in KonferenzbandForschungBegutachtung

Standard

Iterative Learning Control of an Industrial Robot for Neuromuscular Training. / Ketelhut, Maike; Göll, Fabian; Braunstein, Bjoern; Albracht, Kirsten; Dirk, Abel.

CCTA 2019 - 3rd IEEE Conference on Control Technology and Applications: IEEE CCTA 2019, August 19-21, 2019, City University of Hong Kong, Hong Kong, China. 2019. S. 926-932 (CCTA 2019 - 3rd IEEE Conference on Control Technology and Applications).

Publikationen: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitrag - Aufsatz in KonferenzbandForschungBegutachtung

Harvard

Ketelhut, M, Göll, F, Braunstein, B, Albracht, K & Dirk, A 2019, Iterative Learning Control of an Industrial Robot for Neuromuscular Training. in CCTA 2019 - 3rd IEEE Conference on Control Technology and Applications: IEEE CCTA 2019, August 19-21, 2019, City University of Hong Kong, Hong Kong, China. CCTA 2019 - 3rd IEEE Conference on Control Technology and Applications, S. 926-932, IEEE Conference on Control Technology and Applications, Hong Kong, China, 19.08.19. https://doi.org/10.1109/CCTA.2019.8920659

APA

Ketelhut, M., Göll, F., Braunstein, B., Albracht, K., & Dirk, A. (2019). Iterative Learning Control of an Industrial Robot for Neuromuscular Training. in CCTA 2019 - 3rd IEEE Conference on Control Technology and Applications: IEEE CCTA 2019, August 19-21, 2019, City University of Hong Kong, Hong Kong, China (S. 926-932). (CCTA 2019 - 3rd IEEE Conference on Control Technology and Applications). https://doi.org/10.1109/CCTA.2019.8920659

Vancouver

Ketelhut M, Göll F, Braunstein B, Albracht K, Dirk A. Iterative Learning Control of an Industrial Robot for Neuromuscular Training. in CCTA 2019 - 3rd IEEE Conference on Control Technology and Applications: IEEE CCTA 2019, August 19-21, 2019, City University of Hong Kong, Hong Kong, China. 2019. S. 926-932. (CCTA 2019 - 3rd IEEE Conference on Control Technology and Applications). https://doi.org/10.1109/CCTA.2019.8920659

Bibtex

@inbook{50e207bcf5b94e68bc24168e2e25c526,
title = "Iterative Learning Control of an Industrial Robot for Neuromuscular Training",
abstract = "Effective training requires high muscle forces potentially leading to training-induced injuries. Thus, continuous monitoring and controlling of the loadings applied to the musculoskeletal system along the motion trajectory is required. In this paper, a norm-optimal iterative learning control algorithm for the robot-assisted training is developed. The algorithm aims at minimizing the external knee joint moment, which is commonly used to quantify the loading of the medial compartment. To estimate the external knee joint moment, a musculoskeletal lower extremity model is implemented in OpenSim and coupled with a model of an industrial robot and a force plate mounted at its end-effector. The algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee. The results show that the algorithm is able to minimize the external knee joint moment in all three cases and converges after less than seven iterations.",
author = "Maike Ketelhut and Fabian G{\"o}ll and Bjoern Braunstein and Kirsten Albracht and Abel Dirk",
year = "2019",
month = aug,
day = "1",
doi = "10.1109/CCTA.2019.8920659",
language = "Deutsch",
isbn = "9781728127675",
series = "CCTA 2019 - 3rd IEEE Conference on Control Technology and Applications",
pages = "926--932",
booktitle = "CCTA 2019 - 3rd IEEE Conference on Control Technology and Applications",
note = "IEEE Conference on Control Technology and Applications, IEEE CCTA 2019 ; Conference date: 19-08-2019 Through 21-08-2019",

}

RIS

TY - CHAP

T1 - Iterative Learning Control of an Industrial Robot for Neuromuscular Training

AU - Ketelhut, Maike

AU - Göll, Fabian

AU - Braunstein, Bjoern

AU - Albracht, Kirsten

AU - Dirk, Abel

N1 - Conference code: 3

PY - 2019/8/1

Y1 - 2019/8/1

N2 - Effective training requires high muscle forces potentially leading to training-induced injuries. Thus, continuous monitoring and controlling of the loadings applied to the musculoskeletal system along the motion trajectory is required. In this paper, a norm-optimal iterative learning control algorithm for the robot-assisted training is developed. The algorithm aims at minimizing the external knee joint moment, which is commonly used to quantify the loading of the medial compartment. To estimate the external knee joint moment, a musculoskeletal lower extremity model is implemented in OpenSim and coupled with a model of an industrial robot and a force plate mounted at its end-effector. The algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee. The results show that the algorithm is able to minimize the external knee joint moment in all three cases and converges after less than seven iterations.

AB - Effective training requires high muscle forces potentially leading to training-induced injuries. Thus, continuous monitoring and controlling of the loadings applied to the musculoskeletal system along the motion trajectory is required. In this paper, a norm-optimal iterative learning control algorithm for the robot-assisted training is developed. The algorithm aims at minimizing the external knee joint moment, which is commonly used to quantify the loading of the medial compartment. To estimate the external knee joint moment, a musculoskeletal lower extremity model is implemented in OpenSim and coupled with a model of an industrial robot and a force plate mounted at its end-effector. The algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee. The results show that the algorithm is able to minimize the external knee joint moment in all three cases and converges after less than seven iterations.

UR - https://www.mendeley.com/catalogue/b3501e82-2db1-356d-b2fa-ffa2ce7af992/

U2 - 10.1109/CCTA.2019.8920659

DO - 10.1109/CCTA.2019.8920659

M3 - Konferenzbeitrag - Aufsatz in Konferenzband

SN - 9781728127675

T3 - CCTA 2019 - 3rd IEEE Conference on Control Technology and Applications

SP - 926

EP - 932

BT - CCTA 2019 - 3rd IEEE Conference on Control Technology and Applications

T2 - IEEE Conference on Control Technology and Applications

Y2 - 19 August 2019 through 21 August 2019

ER -

ID: 5086378